activity
20172022
most citedA Theoretically Sound Upper Bound on the Triplet Loss for Improving the Efficiency of Deep Distance Metric Learning

8 citations · 22 across the 6 of their papers we have counts for

collaborators

10 papers

cs.CV20221 cited

Collaborative Multi-Teacher Knowledge Distillation for Learning Low Bit-width Deep Neural Networks

Cuong Pham, Tuan Hoang, Thanh-Toan Do

Knowledge distillation which learns a lightweight student model by distilling knowledge from a cumbersome teacher model is an attractive approach for learning compact deep neural n…

cs.CV2019

BTEL: A Binary Tree Encoding Approach for Visual Localization

Huu Le, Tuan Hoang, Michael Milford

Visual localization algorithms have achieved significant improvements in performance thanks to recent advances in camera technology and vision-based techniques. However, there rema…

cs.CV2019

Simultaneous Feature Aggregating and Hashing for Compact Binary Code Learning

Thanh-Toan Do, Khoa Le, Tuan Hoang +3

Representing images by compact hash codes is an attractive approach for large-scale content-based image retrieval. In most state-of-the-art hashing-based image retrieval systems, f…

cs.CV20198 cited

A Theoretically Sound Upper Bound on the Triplet Loss for Improving the Efficiency of Deep Distance Metric Learning

Thanh-Toan Do, Toan Tran, Ian Reid +3

We propose a method that substantially improves the efficiency of deep distance metric learning based on the optimization of the triplet loss function. One epoch of such training p…

cs.CV20196 cited

SDRSAC: Semidefinite-Based Randomized Approach for Robust Point Cloud Registration without Correspondences

Huu Le, Thanh-Toan Do, Tuan Hoang +1

This paper presents a novel randomized algorithm for robust point cloud registration without correspondences. Most existing registration approaches require a set of putative corres…

cs.CV2019

SASSE: Scalable and Adaptable 6-DOF Pose Estimation

Huu Le, Tuan Hoang, Qianggong Zhang +3

Visual localization has become a key enabling component of many place recognition and SLAM systems. Contemporary research has primarily focused on improving accuracy and precision-…